Since its introduction in 1977 as an alternative (or as supplementation) to invasive surgical procedures and/or x-rays, the utilization of MRI in medical diagnosis and treatment has increased dramatically. In this regard, modem MRI techniques produce images with exceptional contrast and which can be rendered in any plane as well as three-dimensionally. Moreover, apart from their imaging quality, MRI techniques are believed to be very safe. For example, MRI techniques do not utilize harmful ionizing radiation but instead rely on the application of magnetic fields and radio frequencies which induce atomic level energy changes which are detectable for assimilation into highly detailed, accurate body (or other object type) images. In contrast, imaging techniques such as computerized tomography scanning (CT scanning) expose patients to significant doses of ionizing radiation which is believed to increase incidences of malignancy. Furthermore, CT techniques cannot reproduce the relative high contrast of an MRI image and have the additional shortcoming of not being able to adequately differentiate between similar but otherwise distinct tissue types (e.g., in particular, if the tissues have similar densities).
The publications and other materials, including patents, used herein to illustrate the invention and, in particular, to provide additional details respecting the practice are incorporated herein by reference. For convenience, the publications are referenced in the following text by author and date and are listed alphabetically by author in the appended bibliography.
The magnetic resonance (MR) signal can be made sensitive to dynamic displacements (“diffusion”) of water at a cellular level and therefore offers a unique insight into tissue structure and organization. Diffusing water molecules typically move approximately 20 μm in 100 ms or 60 μm in 1 s. The collective diffusion movement of the water molecules becomes noticeable as a weakening of the magnetic resonance signal.
Although diffusion measurements were already described in the mid sixties by Stejskal and Tanner, it took almost 30 years for diffusion weighted imaging (DWI) to enter clinical practice (Schaefer et al, 2000). Since then, DWI has proven to be a highly sensitive and specific parameter to detect physiological and patho-physiological changes for many intracranial disease processes (Schaefer et al, 2000), cancer (Charles-Edwards et al, 2006) and for whole body tumor detection (Kwee et al., 2008; Koh et al., 2007). Single-shot echo planar imaging (EPI) techniques are generally considered particularly suitable for DWI since EPI sequences are frequently used for neuroimaging or for mapping microstructural properties of the brain using diffusion tensor imaging (DTI). EPI sequences are highly insensitive to bulk motion and are probably the fastest imaging sequences available, but suffer from spatial distortions caused by magnetic field inhomogenities that may need retrospective correction. A more severe drawback, however, is that with EPI's only rather poor spatial resolution can be achieved and poor coverage for species/samples with short T2. Thus, especially for high resolution imaging of targets with high susceptibility variation, such as the musculoskeletal system (MSK), EPI may not be the method of choice and several other three-dimensional (3D) DWI sequences have been proposed, some of them using the diffusion sensitivity of non-balanced steady-state free precession (SSFP) type of sequences (Miller et al., 2004; Deoni et al, 2004; Mamisch et al, 2008; Welsch et al, 2009; Friedrich et al., 2010). Especially the “Echo” in non-balanced SSFP type sequences (i.e., the refocused signal immediately preceding the RF pulse) is very sensitive to diffusion and represents a unique alternative to standard EPI-based DWI, whereas the “FID” signal (“free-induction decay” signal, i.e., the signal immediately following the radio frequency (RF) pulse) is generally not used, since its sensitivity to diffusion is quite low.
Several models have been developed for the description of diffusion effects in SSFP sequences (Kaiser et al., 1974; Patz et al, 1986; LeBihan et al., 1988; Merboldt et al, 1989; Wu and Buxton, 1990; Buxton, 1993), all of them being based on the seminal work of Kaiser, Bartholdi and Ernst (KBE) (Kaiser et al., 1974). In MRI, besides semi-empirical approaches, such as the one presented by LeBihan (LeBihan et al., 1988), the extension of the so called “KBE ansatz” to pulsed gradient SSFP by Wu and Buxton for MRI pulse sequences (Wu and Buxton, 1990; Buxton, 1993) is generally well accepted and several research groups have examined the effect of an unipolar diffusion sensitizing gradient with SSFP-Echo type of sequences (see FIG. 1a) (Miller et al., 2004; Deoni et al, 2004; Mamisch et al, 2008; Welsch et al, 2009; Friedrich et al., 2010; Patz et al, 1986, Merboldt et al, 1989). Nevertheless, quantification of diffusion effects with SSFP-Echo has not yet found great approval in MRI, since diffusion effects strongly depend on relaxation times (T1, T2). However, it has been shown that diffusion effects are to a leading order independent from T2 for repetition times TR ˜1.5 T2 (Buxton, 1993). As a result, diffusion quantification with SSFP-Echo was shown to be feasible in-vivo, provided T1 is known (Miller et al., 2004). Unfortunately, within this limit, signal to noise ratio (SNR) and scanning efficiency is considerably reduced and far away from what could be considered to be optimal. Nevertheless, the theory of DWI with SSFP-Echo was also extended to anisotropic effects (McNab et al, 2009), allowing to probe for the structure of white matter tracts in the human brain with compelling results.
Another approach to diffusion quantification with SSFP was proposed by Deimling based on a double-echo SSFP (DESS) technique (U.S. Pat. No. 6,891,373, which is incorporated herein by reference in its entirety). Within Deimling's approach, sensitivity to diffusion is achieved via a bipolar gradient waveform, as commonly used with gradient-echo sequences (see FIG. 1b). Deimling proposes to use bipolar gradients noting that unipolar diffusion sensitizing gradients previously lead to complexities in the phase history. In particular, the phase history experienced an expansion via an applied unipolar diffusion gradient so that an assessment of the diffusion coefficient (which thereby depends on the phase history and thus on T1 and T2) is no longer possible. Deimling resolves this problem by using bipolar diffusion sensitizing gradients which offered a simpler diffusion weighting since the expansion caused by the diffusion gradients was compensated by the phase curves. The use of bipolar diffusion sensitizing gradients also led Demling to well-defined diffusion times and allowed him to compensate for the residual T2 weighting by using a combined measurement of the FISP and PSIF signal. In particular, Deimling proposed to use both echoes, namely the free induction decay (FID) (in the following referred to as the S+ signal) and the Echo (the time-reversed FID, in the following referred to as S− signal) within any TR since the signal attenuation from diffusion depends for the echo ratio S−/S+ only on the bipolar gradient waveform (i.e., there is no dependence on relaxation times) and therefore allows a direct assessment of the diffusion constant (D) (Chu, 1989). Demling's diffusion constant (D) is a function of the b-value, which is given by the amplitude (G0) and pulse width (δ) of his bipolar diffusion gradient. However, Demling's method suffers from the rather low sensitivity of the bipolar gradient waveforms to diffusion, generally requiring large moments, therefore long repetition times and thus long scan times.
The use of short repetition times (TR<<T2) with diffusion weighted (dw) SSFP-Echo (FIG. 1a) has shown good promise for the characterization of cartilage function and repair (7): Using a simple semi-quantitative measure, i.e. by taking the ratio of a diffusion and a non-diffusion weighted SSFP-Echo acquisition, in-vivo high-resolution DWI of cartilage was shown to complement the information of T2-mapping or dGEMRIC. As compared to other “true” quantitative mapping techniques, such as T2, T1rho, and dGEMRIC, however, some ambiguity of the semi-quantitative DWI approach with SSFP arises in the interpretation of results due to the confounding influence of longitudinal and transverse relaxation.
Diffusion sensitized (“weighted”) SSFP-Echo has shown great promise and compelling results were demonstrated with a signal to noise ratio (SNR) and contrast to noise ratio (CNR) efficiency that outperforms other 3D diffusion weighted spin echo (SE) techniques. Nevertheless there is much room for optimization and further development: Generally, non-balanced SSFP is prone to motion and for successful in-vivo quantification of diffusion effects, frequently, navigator-based correction methods are applied (Miller et al., 2004). Furthermore, for state-of-the-art SSFP-Echo based DWI, repetition times at least similar to T2 must be chosen in order to allow for quantification (provided T1 is known) and the accuracy of quantification increases with increasing flip angles. Typically, however, a short TR<<T2 is much more desirable since this not only reduces sensitivity to bulk motion but also increases SNR, reduces scan times, and thus allows scans with increased resolution.
Thus, there remains of a need for fast quantitative SSFP-based DWI with short TRs. In particular for targets of high susceptibility variation, there is a need for high-resolution quantitative diffusion MRI sequences with short and thus clinically practicable scan times.
More in particular, from the above, it is apparent that there exists a need in the art for imaging methods and/or apparatus which solve or at least ameliorate one or more of the above drawbacks of the prior art. It is a purpose of this invention to fulfill these needs as well as other needs which will become more apparent to the skilled artisan once given the following disclosure.